Along with development of computer network technologies and mobile technologies, search services have been more and more extensively applied. In addition to network-wide searches conducted on professional search websites, most websites have capabilities to conduct searches on local websites. For websites having abundant data, such as shopping websites, it is particularly important for a website to grow its businesses by finding desired search results based on keywords input by users.
According to conventional search methods, a search server conducts searches in a website database that might have a large number of items or data objects. These searches are conducted based on keywords to obtain the data objects matching the keywords. To better present useful information to users, correlations of search results corresponding to keywords may be calculated respectively. The search results are then ranked based on correlations.
The conventional search methods obtain search results and display them in an order. Some useful information may be arranged at bottom positions if search results are sorted base only on literal correlations with keywords. For example, suppose that the query is “Brand A cell phone,” and the search server finds two search results. The first search result is a webpage that briefly describes the “Brand A cell phone”, and the second search result is a webpage with texts and images to describes the “Brand A cell phone” and a “Brand B cell phone”. For literal correlations, the first search result has a higher correlation than the second search result does. On a specific website, such as a shopping website, the second search result has more useful information than the first search result. The second search result therefore can better meet search needs of users. Therefore, search results sorted based only on literal correlations with keywords may not match the user's needs.